Perception Engineer - Apprentice at Origin

Bengaluru, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

24 Apr, 26

Salary

0.0

Posted On

24 Jan, 26

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python 3.x, C++17/20, ROS 2, Deep-Learning Vision, Point-Cloud Processing, Camera-LiDAR Calibration, RANSAC, SLAM, TensorRT, ONNX Runtime, CNN, Transformer Models, IMU, Kalman, ICP, PCL, Open3D

Industry

Robotics Engineering

Description

As a Perception Engineering Intern / Apprentice at Origin (Formerly 10xConstruction), you will help our autonomous drywall-finishing robots "see" the job-site. You'll design and deploy perception pipelines—camera + LiDAR fusion, deep-learning vision models, and point-cloud geometry—to give the robot the awareness it needs. Key Responsibilities * Build ROS 2 nodes for 3-D point-cloud ingestion, filtering, voxelisation and wall-plane extraction (PCL / Open3D). * Train and integrate CNN / Transformer models for surface-defect detection and semantic segmentation. * Implement RANSAC-based pose, plane and key-point estimation; refine with ICP or Kalman/EKF loops. * Fuse LiDAR, depth camera, IMU and wheel odometry data for robust SLAM and obstacle avoidance. * Optimize and benchmark models on Jetson-class edge devices with TensorRT / ONNX Runtime. * Collect, label and augment real & synthetic datasets; automate experiment tracking (Weights & Biases, MLflow). * Collaborate with manipulation, navigation and cloud teams to ship end-to-end, production-ready perception stacks. Qualifications & Skills * Solid grasp of linear algebra, probability and geometry; coursework or projects in CV or robotics perception. * Proficient in **Python 3.x and C++17/20**; comfortable with git and CI workflows. * Experience with **ROS 2 (rclcpp / rclpy)** and custom message / launch setups. * Familiarity with **deep-learning vision** (PyTorch or TensorFlow)—classification, detection or segmentation. * Hands-on work with **point-cloud processing** (PCL, Open3D); know when to apply voxel grids, KD-trees, RANSAC or ICP. * Bonus: exposure to camera–LiDAR calibration, or real-time optimization libraries (Ceres, GTSAM). Why Join Us * Work side-by-side with founders and senior engineers to redefine robotics in construction. * Build tech that replaces dangerous, repetitive wall-finishing labor with intelligent autonomous systems. * Help shape not just a product, but an entire company—and see your code on real robots at active job-sites. Python 3.x C++17/20 ROS 2 PyTorch Open3D RANSAC

Responsibilities

The role involves designing and deploying perception pipelines for autonomous drywall-finishing robots. Key tasks include building ROS 2 nodes, training deep-learning models, and collaborating with various teams to create production-ready perception stacks.